A Parsimonious Four-Variable Nomogram for Predicting Lower-Extremity Amputation in Patients with Type 2 Diabetes and Diabetic Foot Ulcers: Development and Internal Validation Using Dual-Method Stability-Based Variable Selection

Abstract

Background Diabetic foot ulcers (DFUs) remain the leading cause of non-traumatic lower-extremity amputation (LEA). Most published risk-stratification tools require specialized testing and are difficult to apply in routine practice. We sought to build a simple nomogram for amputation risk using only routinely available clinical indicators. Methods This single-center retrospective cohort study included 508 hospitalized patients with type 2 diabetes-related DFUs treated between January 2019 and June 2025. The cohort was randomly split into training (n=357, 84 amputations) and validation (n=151, 35 amputations) sets at a 7:3 ratio with stratification on outcome. The outcome was lower-extremity amputation (minor or major) during the index hospitalization. Twenty-four baseline variables were screened for selection in the training set (84 events) using two independent methods: LASSO regression with 10-fold cross-validation (at λ.1se) and 1000 bootstrap stepwise logistic regression replicates (selection frequency >80%). Variables retained by both methods were entered into the final multivariable logistic regression model, from which a nomogram was constructed. Discrimination was assessed by the area under the receiver operating characteristic curve (AUC); calibration was evaluated using calibration plots, the Hosmer–Lemeshow test, and the calibration slope; and clinical utility was assessed by decision curve analysis (DCA). Internal validity was further examined by bootstrap resampling with optimism correction. Results Four variables were retained by both LASSO and bootstrap screening: serum albumin (protective), platelet count, smoking history, and hypertension (predictors of higher risk). The nomogram achieved an AUC of 0.788 (95% CI 0.735–0.840) in the training cohort and 0.755 (95% CI 0.671–0.839) in the validation cohort; the wide validation confidence interval reflects the limited number of validation events (n = 35). On bootstrap internal validation (1000 resamples), the optimism-corrected AUC was 0.776. Calibration was acceptable in both cohorts (Hosmer–Lemeshow P = 0.794; calibration slope 0.944 [bootstrap-corrected]), and DCA suggested potential clinical utility. Conclusion A four-variable nomogram based on serum albumin, platelet count, smoking history, and hypertension estimated in-hospital LEA risk in hospitalised patients with type 2 diabetes-related DFUs with moderate discrimination and acceptable calibration, and decision curve analysis suggested potential clinical utility. Because every predictor is available from routine clinical history and standard laboratory testing, the model may support early in-hospital risk stratification rather than treatment decisions. As this was a single-centre study with internal validation only, external multi-centre validation is required before routine clinical use.